Mine hunting is traditionally performed by a combination of acoustic methods (i.e., sonar) and optical methods. Traditionally, detection and classification of mine-like contacts are performed by acoustical methods. During such operations, “contacts” are classified as “mine-like” only if they are sufficiently similar to known signatures of mines. Many of the sonar contacts classified as “mine-like” will, in fact, be “false alarms”. That is, they will be objects that are not mines. This is especially true in highly cluttered areas. A coral reef is an area where acoustical methods are expected to generate many false alarms. This is due to the massive amounts of “biological clutter” in the scene.
Detection/classification is traditionally followed by an identification step, where each “mine-like contact” is evaluated to determine if it is or is not a mine. Typically, the identification process is carried out by optical methods. A variety of optical methods may be employed, ranging from divers who visually identify the contacts, to remotely operated vehicles equipped with video cameras, to towed bodies or autonomous vehicles equipped with more sophisticated Laser Line Scan, Streak Tube Imaging Lidar (STIL), or other lidar sensors. If the density of “mine-like contacts” to be identified is low, identification can be manually performed by a trained human observer on an image-by-image basis. However, in a coral reef (or other highly cluttered environment) where the density of “mine-like contacts” is high, this process is very time consuming and tiring. It is highly desirable to develop an automated method that will locate the manmade objects in an image, while rejecting the coral reef (or other clutter) in the image. Then the human observer will be cued to focus his attention on only the manmade objects in the scene for identification as mines or non-mines.